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kevynf

AKBridge MCP Server

by kevynf

stock_financial_analysis_indicator

Read-onlyIdempotent

Fetch a stock's financial analysis indicators from Sina Finance for a given symbol and start year to assess profitability, growth, and solvency.

Instructions

新浪财经-财务分析-财务指标 https://money.finance.sina.com.cn/corp/go.php/vFD_FinancialGuideLine/stockid/600004/ctrl/2019/displaytype/4.phtml :param symbol: 股票代码 :type symbol: str :param start_year: 开始年份 :type start_year: str :return: 新浪财经-财务分析-财务指标 :rtype: pandas.DataFrame

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolNo600004
start_yearNo1900
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so safety behavior is covered. The description adds the source URL and a pandas DataFrame return type, but gives no further details on what the indicator output contains, date-range behavior, or any constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and structured as a docstring with a source URL, labeled parameters, and return type. It contains a redundant repeat of the title in the return line, but the overall size is appropriate for the tool's simplicity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, and the description only says the result is a DataFrame of 'financial indicators' without listing fields, period granularity, or any caveats. The two-parameter surface is simple, but the missing output details and absent sibling differentiation make it incomplete for confident selection.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the docstring's 'symbol: 股票代码' and 'start_year: 开始年份' provide basic meaning beyond the bare property names. However, they are minimal translations and do not explain value formats, the default 1900 semantics, or how start_year bounds the returned periods.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with the same noun phrase as the title—'新浪财经-财务分析-财务指标'—and adds a URL, but it never states an action like 'fetches' or 'queries'. The resource and source are identifiable, yet the lack of a verb and no explicit comparison to the similar sibling 'stock_financial_analysis_indicator_em' leaves the purpose somewhat vague.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no 'when to use this vs alternatives' guidance. The description only lists parameters and a return type; it does not say when this Sina-based indicator tool should be preferred over siblings like stock_financial_analysis_indicator_em or stock_financial_abstract.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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